Predicting SARS-CoV-2 Infection Trend Using Technical Analysis Indicators

  1. Marino Paroli
  2. Maria Isabella Sirinian

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Abstract

Objectives:

Coronavirus disease 2019 (COVID-19) pandemic is a global health emergency caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to evaluate whether technical analysis (TA) indicators, commonly used in the financial market to spot security price trend reversals, might be proficiently used also to anticipate a possible increase of SARS-Cov-2 spread.

Methods:

Analysis was performed on datasets from Italy, Iran, and Brazil. TA indicators tested were: (1) the combined use of a faster (3-d) and a slower (20-d) simple moving averages (SMA), (2) the moving average converge/divergence (MACD), and (3) the divergence in the direction of the number of new daily cases trend and the corresponding MACD histogram.

Results:

We found that the use of both fast/slow SMAs and MACD provided a reliable signal of trend inversion of SARS-Cov-2 spread. Results were consistent for all the 3 countries considered. The trend reversals signaled by the indicators were always followed by a sustained trend persistence until a new signal of reversal appeared.

Conclusions:

TA indicators tested here proved to be reliable tools to identify in the short mid-term a subsequent change of direction of viral spread trend either downward, upward, or sideward.

Article activity feed

  1. Version published to 10.1017/dmp.2020.254
  2. ScreenIT

    SciScore for 10.1101/2020.05.13.20100784: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All TA indicators were calculated according to the appropriate formula using the Microsoft Excel spreadsheet program.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    A major limitation of this study is the intrinsic nature of the data. The reported number of daily new cases is at least in part inaccurate since a consistent number of new infections can be missed due to the presence of asymptomatic subjects (10). Underreporting of cases due to several factors is a major limitation of any epidemiological model. Moreover, the number of diagnostic tests taken daily may fluctuate significantly. It is worth to note that the number of tests does not refer to the same in each country. One main difference is that some countries report the number of people tested, while others report the number of tests which can be higher if the same person is tested more than once. Finally, the incidence of infection can vary among areas of the same country not necessarily reflecting the situation of the whole country (11). This has been particularly evident in Italy where in Lombardy region cases account for about half of total cases of Italy. Nevertheless, we suggest that TA indicators might provide reliable real-time information of how SARS-Cov-2 infection is spreading to rush the set-up of new containment measures by governments when needed.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  3. Version published to 10.1101/2020.05.13.20100784v2 on medRxiv
  4. Version published to 10.1101/2020.05.13.20100784v1 on medRxiv